Future work, part 2: absolute vs. relative progress. April 2, 2017 Snippets
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In last week’s Snippets, we grappled with the idea that if we want to describe and understand how broad groups of people choose to spend their time, perceived progress against challenge might be a good place to start. With increasing numbers of young men opting out of the workforce in favor of video games and other “alternative” challenges, the looming backdrop of automation beckons: is this a glimpse of what’s to come? Is Keynes’s future, or a warped version of it, already here?
Meanwhile, that backdrop was pulled into sharp relief as Treasury Secretary Steve Mnuchin in an interview with Mike Allen from Axios suggested that it’ll take 50–100 more years, in his words, “until the country faces a labor crisis at the hands of automation.” That specific phrase, along with the line “not even on my radar screen”, fetched a swift and angry response from the tech community, which showed the kind of wounded indignation that often follows those ridiculous statements that just might contain an annoying shard of truth (e.g. Apple loyalists when someone suggests, “You know it’s all just marketing”):
Tech community “dumbfounded” by Mnuchin’s dismissal of AI on jobs | Kim Hart, Axios
What does seem clear is that the current administration does not seem to view artificial intelligence as something that needs to be actively managed by the government, at least not for the time being. As Joe Xie offered on Twitter, an alternate take of Mnuchin’s comments might be considered to read: “There will be no foreseeable regulations to limit the potential of AI, robotics and automation.” In other words, it’s a fair fight we want, so it’s a fair fight we shall have. But a fair fight over what exactly? Over work? Or over something else? It’s still the early days, but if it’s a fight over productivity then the early numbers don’t look so good for team human workers.
It’s tempting for us in the tech community to think of this problem on an individual scale — job A disappears; job B appears anew. But the labor market isn’t completely mobile or elastic — most people can’t easily move locations, retrain, or simply snap from one job to another if you’re not a creative professional working in a big city. And there’s little doubt that this friction will have secondary consequences down the road with regard to our relationship with our coworkers and competitors, when the time comes. It’s certainly fine for us to be on alert against paper clip apocalypse scenarios, but we should also be worried about other kinds of bad outcomes, so we might be more prepared.
We’ve still got a little bit of time before non-human minds begin truly competing with human minds in ernest, so we might as well use that time to figure out how those two kinds of minds will be similar and different from one another. It may turn out that one fundamental difference between artificial and human minds will be that the former care more about absolute progress against a challenge, while the latter care more about relative progress. That is a tremendous difference, and possibly the one of the best hopes for how those two types of minds might ultimately be more collaborative than competitive in the long run. If we’re looking for practical things we can do now to ensure a future full of motivation and personal satisfaction for the average human being, where all can strive towards their own chosen version of perceived progress against challenge, perhaps that’s something we should contemplate.
This week’s podcast episodes for your enjoyment: special AI edition
How AI beat the pros at Texas Hold’em, and why it matters | The AI Podcast with NVIDIA
Interactive machine learning systems with Alekh Agarwal | This Week in Machine Learning & AI
Some surprising ways that businesses are making money:
Airlines make more money selling miles than seats | Justin Bachman, Bloomberg
The high-speed trading behind your Amazon purchase | Christopher Mims, WSJ
Alternative facts:
The satirical origins of the meritocracy | Jason Kottke
The facts are true; the news is fake | Nassim Nicholas Taleb
The controversial, American, Ghost in the Shell | Anthony Lane, The New Yorker
Pioneering:
The new virtual accelerator | Ty Danco
More reading from around the Internet:
Which productivity puzzle? Why we’re asking many of the wrong questions | Bill Janeway
Behind the decline at China’s tech giant Baidu | Juro Osawa & Yunan Zhang, The Information
Learning curves sloping up and down | Eugene Wei
Some things I have learned about email | Albert Wenger
The artificial services economy | Dan Ramsden
The geography of US productivity | Bourree Lam, The Atlantic
JP Morgan set to run first apps in public cloud | Kim Nash, WSJ
And just for fun:
In this week’s news and notes from the Social Capital family, big things are coming out of the data supply chain pioneers at mParticle. CEO Michael Katz, when describing mParticle, likes to explain the evolution of data platforms as coming in waves. The first wave coincided with the rise of cable TV and the need to capture point-of-sale data to inform targeting and promotions; the second with the evolution of the digital media ecosystem on the web, where customers could be tracked across websites, grouped into cohorts, and understood based on their browsing habits. Web-centric and ad-focused data platforms were the norm, and they’ve lasted until today. But as Michael tells us:
“The tools that previously helped brands navigate web challenges are simply not suited for the unique challenges in a mobile world. Today, large companies routinely employ dozens of SaaS tools within and across their CRM, marketing, sales, business intelligence, and customer support functions (as well as many other parts of the business). In fact, according to a recent survey by the software database firm Siftery, the average number of software vendors used by a typical large company has increased by 20x in just 10 years. While SaaS tools give businesses the cost saving and speed they desire, it means that valuable customer data is siloed in these tools. We started mParticle because we saw the shift to mobile plus the fragmentation of data across SaaS tools as catalyzing a need for a new kind of data platform — the third wave.”
Welcome to the third wave of data platforms | Michael Katz, mParticle
Katz’s vision of a third wave of mobile data platforms is most certainly coming true, and mParticle’s foresight into those challenges has turned into a fast-growing business with a huge mission ahead of them. The big recent news is that mParticle has released several invaluable upgrades to their core stable of products since the beginning of this year. Data Filters, Feeds, and most recently Custom Rules that let your team personalize the flow of information across your company’s internal data supply chain with greater flexibility than ever before. Every tool speaks their own language, so when one system calls a “checkout” what another calls a “completed transaction”, and data lakes start to turn into data swamps, mParticle’s quick internal rules customization allows for automated data transformation right as it’s ingested, shielding their customers from small annoyances to large potential conflicts.
Forbes recently listed them among their 20 technologies for B2B buyers to check out this year, along with heavyweights like Asana and Slack:
20 B2B technologies to try in 2017 | Dan Reich, Forbes
And mParticle’s blog remains a tremendous resource for anyone in digital marketing, customer data, growth, app engineering, and more. If you want to get on board the mParticle train, they’re currently hiring for business development, sales and services positions in both New York and San Francisco.
Have a great week,
Alex & the team at Social Capital
